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1.
Guang Pu Xue Yu Guang Pu Fen Xi ; 30(10): 2628-31, 2010 Oct.
Artigo em Chinês | MEDLINE | ID: mdl-21137387

RESUMO

For a quick and noninvasive examination of the tongue for potential hepatitis patients, a study was conducted on the relation between the reflectivity of near infrared spectrum on the tongues of the healthy people and the hepatitis patients. Spectral data, 25 items for each case, are to be collected from the left and right side tongue, left and right sublingual venae, and tip of the tongue from the healthy people and the hepatitis patients. Then a three-layer neural network structure was established with all the data input after normalization reflectivity pretreatment. With the establishment of a BP neural network model, 40 data from each part of the body were selected as training samples. The rest 10 were adopted for prediction, which later was proved to be 100% correct with relative deviation values of less than 0.2. The research findings show that the proposed application of BP neural network in the spectral noninvasive examination of the tongue for identification of different case diagnosis is important for reference.


Assuntos
Hepatite/diagnóstico , Redes Neurais de Computação , Espectroscopia de Luz Próxima ao Infravermelho , Língua , Diagnóstico Diferencial , Humanos , Medicina Tradicional Chinesa
2.
Guang Pu Xue Yu Guang Pu Fen Xi ; 30(10): 2748-51, 2010 Oct.
Artigo em Chinês | MEDLINE | ID: mdl-21137413

RESUMO

In order to diagnose fatty liver noninvasively, rapidly and accurately, this article presented a new method based on spectroscopy to diagnose fatty liver. This method is non-invasive, rapid. Because tongue can objectively reflect physiological and pathological changes, so this experiment collected reflectance spectrum on the tongue tips of volunteers at first, then analyzed the above data, calculated the normalized reflection ratio, and built a three-layer BP network model. Thirty two healthy people and 44 fatty liver sufferers were chosen randomly from the total 115 samples and their data were input into neural network, then the data of unknown samples of 14 healthy and 25 fatty liver ones were input into the model, and the classification accuracy was 89.7%. This result approved the feasibility of using spectroscopy to diagnose fatty liver. Meanwhile, the result showed that spectral method can reflect the information of organization and tiny circulation taken by tongue more objectively. This method may provide a fast and simple diagnostic tools for clinic, and also can provide a reference to the syndrome measurement of the traditional Chinese medicine.


Assuntos
Fígado Gorduroso/diagnóstico , Redes Neurais de Computação , Análise Espectral , Humanos , Medicina Tradicional Chinesa , Modelos Teóricos , Língua
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